Econometrics

Basic Information

1. Course Type: Compulsory Major Course

2. Class Hours: 54 (45 minutes each class hour)

3. Credits: 3 credits

4. Suitable for: Graduate Students Majored in Finance

Course Introduction

This course systemically introduces the basic theories, thoughts, methods and applications of econometrics. The course aims to help students understand the idea of econometric model and grasp the commonly used econometric models. Topics include classical econometric model, stationary time-series model, non-stationary time series model, vector auto regression model, co - integration and error correction model and GARCH family models.

Course Objectives

The course aims to help students understand the idea of econometric models and grasp the commonly used econometric models. During this course, the students will learn to use the econometric model to analyze problems in the field of economy and solve practical problems. The course trains students basic quantification skills through all kinds of economic issues, improves the students' mathematical analysis level, especially the student's ability to study all kinds of economic problems and the ability of comprehensive analysis. This course not just introduces the basic theory of econometrics, but also allows students to participate in the whole process of building up econometric models, so that students can use methods and techniques of econometric models to better solve practical problems in the future.

Outline of Course Content

Chapter 1 Classical econometric model

Overall Objective:

1. The principle of Ordinary Least Squares and the process of establishing the linear regression model.

2. How to test and remedy heteroscedasticity, autocorrelation and multicollinearity, and demonstrate to establish a multiple linear regression model using EVIEWS.

Contents:

Section1. Linear regression model and its estimation

Section2. Contrary to the basic assumptions

Chapter 2  Stationary time-series model

Overall Objective:

1. How to establish AR model, MA model and ARMA model using of stationary time-series.

2. How to use EVIEWS to realize this process

Contents:

Section1. Autoregressive mode

Section2. Moving average model

Section3.Autoregressive moving average model

Chapter 3 Non-stationary time series model

Overall Objective:

1. How to judge the stationary of time-series

2. How to establish a model by using non-stationary time-series

3. How to use EVIEWS to realize this process

Contents:

Section1. Identification of time series stationary

Section2. Deterministic trend of time series model

Section3. Stochastic trend of time series model

Chapter 4  Vector auto regression model

Overall Objective:

1. How to establish VAR model

2. How to make impulse response analysis and variance decomposition

3. How to use EVIEWS to realize this process

Contents:

Section1. The introduction to the VAR model

Section2. Estimation of VAR model and related test

Section3. Impulse response analysis

Section4. Variance decomposition

Chapter 5 Co - integration and error correction model

Overall Objective:

1. How to establish the co - integration and error correction model, including the Engle-Granger co - integration analysis and Johnsen co - integration analysis.

2. How to use EVIEWS to realize this process.

Contents:

Section1. Engle-Granger co - integration analysis method

Section2. Johnsen co - integration analysis method

Chapter 6 GARCH family models

Overall Objective:

1. The GARCH model and its various deformations

2. How to use EVIEWS to realize this process

Contents:

Section1. ARCH (Autoregressive conditional heteroskedasticity) model

Section2. the GARCH model

Section3.Other forms of the GARCH model

Class Hours Distribution

Week 1 to 5 Chapter 1

Week 6 Lab course

Week 7 and 8 Chapter 2

Week 9 Chapter3

Week 10 Lab course

Week 11 to 12 Chapter4

Week 13 Lab course

Week 14 to 15 Chapter5

Week 16 Lab course

Week 17 and 18 Chapter6

The total course hour is 54(45 minutes each class hour), which will be evenly distributed in 18weeks, that is every week will have 3 course hours.

Text book

Financial Econometrics: From the Perspective of Time Series Analysis, Zhang Chengsi, Renmin University of China Press.2013

Course requirements and grading

Grading Policy: Your grade for the course will be calculated as follows:

Regular Homework and Class Participation 30%

Final Exam  70%

Attendance: Regular attendance is an important requirement for successful performance in this course. If a student repeatedly misses classes, questions will be raised with the administration and suggesting the student withdrew from the course.

Homework problems: problem sets will be assigned regularly. All of the students will get a chance to present homework solutions in class. At this point, it is not as important to have a correct solution as it is to demonstrate that you have worked on your homework seriously. Please, start looking at problems right away so that you can ask for help if you need it. In addition to my office hours and email, you can use the homework discussion board on Blackboard for homework help. Your homework problems will help you to understand the material and to systematically prepare for exams. Class participation and homework will account for 30% of your grade.